Design Method for Numerical Function Generators Based on Polynomial Approximation for FPGA Implementation
Abstract
This paper focuses on numerical function generators (NFGs) based on k-th order polynomial approximations. We show that increasing the polynomial order k reduces signi cantly the NFG's memory size. However, larger k requires more logic elements and multipliers. To quantify this tradeoff, we introduce the FPGA utilization measure, and then determine the optimum polynomial order k. Experimental results show that: 1) for low accuracies (up to 17 bits), 1st order polynomial approximations produce the most ef cient implementations; and 2) for higher accuracies (18 to 24 bits), 2nd-order polynomial approximations produce the most ef cient implementations.
Document Details
- Document Type
- Technical Report
- Publication Date
- Aug 01, 2007
- Accession Number
- ADA596239
Entities
People
- Jon T. Butler
- Shinobu Nagayama
- Tsutomu Sasao
Organizations
- Naval Postgraduate School